The invention relates generally to the field of medical image data storage. More particularly, the invention relates to a technique for reducing the amount of medical image data of a dynamic medical image data set that is stored in long-term data storage.
Picture archiving and communications systems, or PACS, have become an extremely important component in the management of digitized image data, particularly in the field of medical imaging. Such systems often function as central repositories of image data, receiving the data from various sources, such as medical imaging systems. The image data is stored and made available to radiologists, diagnosing and referring physicians, and other specialists via network links. Improvements in PACS have led to dramatic advances in the volumes of image data available, and have facilitated loading and transferring of voluminous data files both within institutions and between the central storage location and remote clients.
In the medical diagnostics field, depending upon the imaging modality, digitized data may be acquired and processed for a substantial number of images in a single examination, each image representing a large data set defining discrete picture elements (pixels) of a reconstructed image, or volume elements (voxels) in three dimensional data sets. Computed tomography (CT) imaging systems, for example, can produce numerous separate images along an anatomy of interest in a very short examination timeframe. Other imaging modalities are similarly capable of producing large volumes of useful image data, including magnetic resonance imaging (MRI) systems, digital X-ray systems, X-ray tomosynthesis systems, ultrasound systems, positron emission tomography (PET) systems, and so forth. Ideally, all such images are stored centrally on the PACS, and made available to the radiologist for review and diagnosis.
A dynamic image data set can produce even greater amounts of image data. Dynamic imaging acquires a volume of data at multiple points in time to create a four-dimensional image. One purpose of dynamic imaging is to access the change over time of either a patient's anatomy or function. One example of an anatomical change might be a cardiac exam to measure ejection fraction. An example of a functional change is a perfusion study. The difference between the two is that functional examinations require holding the anatomy fixed, which may require non-rigid image registration to warp the anatomy into correspondence for each image at each moment in time. An example is dynamic contrast-enhanced magnetic resonance (MR) imaging, where the tissue's uptake of a contrast agent over time is studied.
Various techniques have been proposed and are currently in use for analyzing and compressing large data files, such as medical image data files. Image data files typically include streams of data descriptive of image characteristics, typically of intensities or other characteristics of individual pixels or voxels in the reconstructed image. In the medical diagnostic field, these image files are typically created during an image acquisition, encoding or processing (e.g., reconstruction) sequence, such as in an X-ray, MRI, CT, or other system, or in a processing station designed to process image data from such systems. The image data may be subsequently processed or reprocessed, such as to adjust dynamic ranges, or to enhance certain features shown in the image, for storage, transmittal and display.
While image files may be stored in raw and processed formats, many image files are quite large, and would occupy considerable disc or storage space. Moreover, an almost exponential increase in the resolutions of imaging systems has occurred and which appears will continue into the future, leading to the creation of ever larger image files, typically including more data as a result of the useful dynamic range of the imaging system, the size of the matrix of image pixels and voxels, and the number of images acquired per examination. In addition, the processing and memory requirements for current PACS systems for new clinical applications and techniques is beginning to tax current system capabilities, such as the ever increasing clinical needs for volumetric data sampled over time and for the use of multiple energy volumes for better visualization of anatomical and functional features.
In addition to occupying large segments of available memory, large image files can be difficult or time consuming to transmit from one location to another. In a typical medical imaging application, for example, a scanner or other imaging device will typically create raw data which may be at least partially processed at the scanner. The data is then transmitted to other image processing circuitry, typically including a programmed computer, where the image data is further processed and enhanced. Ultimately, the image data is stored either locally at the system, or in the PACS for later retrieval and analysis. In all of these data transmission steps, the large image data file must be accessed and transmitted from one device to another.
Current image handling techniques include compression of image data within the PACS environment to reduce the storage requirements and transmission times. Such compression techniques generally, however, compress entire files, including descriptive header information which could be useful in accessing or correlating images for review. Moreover, current techniques may not offer sufficiently rapid compression and decompression of image files to satisfy increasing demands on system throughput rates and access times. Finally, alternative compression and decompression techniques do not offer the desired compression ratios, in combination with rapid compression and decompression in a client-server environment.
Another drawback of existing compression techniques is that only certain portions of a medical image may be relevant for diagnosis or treatment. Thus, considerable storage space in a PACS may be allocated to the storage of medical image data that is irrelevant for the patient's diagnosis and treatment. This problem becomes even more acute as imaging systems achieve greater and greater resolutions, which correspond to a need for even more data storage space.
There is a need, therefore, for an improved image data compression and decompression technique which provides rapid compression and decompression of image files, such as dynamic image files, and which obtains improved compression ratios and transmission times. Furthermore, there is a particular need for a technique to enable image data storage systems to accommodate the increase in data required to store medical images obtained with ever increasing resolutions of imaging systems.